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Improved Generalized Synthetic Estimator for Domain Mean
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In this paper, we have proposed an estimator for domain mean using auxiliary character when domain mean of the auxiliary character is unknown. The some members of the proposed estimator for domain mean using auxiliary character with unknown domain mean are studied. The expressions for bias and mean square error of the proposed estimator have been studied. The value of the minimum mean square error of the proposed estimator has been explained with the relevant estimators. The proposed estimator is found more efficient than the relevant estimators. The simulation study is also obtained in the terms of an absolute relative bias and simulated relative standard error using the data (Sarndal et al. (1992, Appendix B)). The simulation study shows that the proposed estimator is more efficient than the relevant estimators for those domains for which the synthetic assumption of the proposed estimator meet closely.
The Netherlands Press
Title: Improved Generalized Synthetic Estimator for Domain Mean
Description:
In this paper, we have proposed an estimator for domain mean using auxiliary character when domain mean of the auxiliary character is unknown.
The some members of the proposed estimator for domain mean using auxiliary character with unknown domain mean are studied.
The expressions for bias and mean square error of the proposed estimator have been studied.
The value of the minimum mean square error of the proposed estimator has been explained with the relevant estimators.
The proposed estimator is found more efficient than the relevant estimators.
The simulation study is also obtained in the terms of an absolute relative bias and simulated relative standard error using the data (Sarndal et al.
(1992, Appendix B)).
The simulation study shows that the proposed estimator is more efficient than the relevant estimators for those domains for which the synthetic assumption of the proposed estimator meet closely.
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